Author(s)

Emmanuel Alphonsus Akpan^1*, K. E. Lasisi¹, Ali Adamu², Haruna Bakari Rann³

¹Department of Mathematical Science, Abubakar Tafawa Balewa University, Bauchi, Nigeria.
²Federal College of Education (Tech.), Gombe, Gombe State, Nigeria.
³Department of Mathematics and Statistics, University of Maiduguri, Maiduguri, Nigeria.

The study explored both Box and Jenkins, and iterative outlier detection procedures in determining the efficiency of ARIMA-GARCH-type models in the presence of outliers using the daily closing share price returns series of four prominent banks in Nigeria (Skye (Polaris) bank, Sterling bank, Unity bank and Zenith bank) from January 3, 2006 to November 24, 2016. The series consists of 2690 observations for each bank. The data were obtained from the Nigerian Stock Exchange. Unconditional variance and kurtosis coefficient were used as criteria for measuring the efficiency of ARIMA-GARCH-type models and our findings revealed that kurtosis is a better criterion (as it is a true measure of outliers) than the unconditional variance (as it can be depleted or amplified by outliers). Specifically, the strength of this study is in showing the applicability and relevance of iterative methods in time series modeling.

Heteroscedasticity, Kurtosis, Model Efficiency, Outliers, Unconditional Variance, Volatility

Akpan, E. , Lasisi, K. , Adamu, A. and Rann, H. (2019) Application of Iterative Approaches in Modeling the Efficiency of ARIMA-GARCH Processes in the Presence of Outliers. Applied Mathematics, 10, 138-158. doi: 10.4236/am.2019.103012.